2 papers
cs.LG2025
Metric Privacy in Federated Learning for Medical Imaging: Improving Convergence and Preventing Client Inference Attacks
Judith Sáinz-Pardo Díaz, Andreas Athanasiou, Kangsoo Jung +2
Federated learning is a distributed learning technique that allows training a global model with the participation of different data owners without the need to share raw data. This…
cs.LG2025
Enhancing the Convergence of Federated Learning Aggregation Strategies with Limited Data
Judith Sáinz-Pardo Díaz, Álvaro López García
The development of deep learning techniques is a leading field applied to cases in which medical data is used, particularly in cases of image diagnosis. This type of data has priva…